Development of a real-time PCR-based system targeting the 16S rRNA gene sequence for rapid detection of Alicyclobacillus spp. in juice products

Connor, Christopher; Luo, Huibo; Gardener, Brian B. McSpadden; Wang, Hua H.

doi:10.1016/j.ijfoodmicro.2004.08.016

Cited by 57 publications

(40 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The GenBank record also lists this as from strain DSM 3922, but a strain mix-up in the culture supplied by the DSMZ was reported in 1992 (27). The type strain (ATCC 49025, listed by the DSMZ as equivalent to DSM 3922) was resequenced in 2005 (AY573797 [9]). These two sequences are 14% different, and X60602 is now described by GenBank as from a Bacillus sp.…”

Section: Discussionmentioning

confidence: 99%

Naïve Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy

Wang

Tiedje

Cole

2007

Appl Environ Microbiol

16,947

11,815

View full text Add to dashboard Cite

The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (>95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and Starting in the mid-1980s, Carl Woese revolutionized the field of microbiology with his rRNA-based phylogenetic comparisons delineating the three main branches of life (28). Today, rRNA-based analysis remains a central method in microbiology, used not only to explore microbial diversity but also as a day-to-day method for bacterial identification. Identification methods are conceptually easier to interpret than molecular phylogenetic analyses and are often preferred when the groups are well understood. Most rRNA identification (classification) methods, as opposed to phylogenetic (clustering) methods, have been nearest-neighbor-based classification schemes (10, 18; however, see reference 4). In some part, this was due to the lack of a consistent, higher-level bacterial classification structure (taxonomy). Several recent events have helped change this situation. In 2002, an ad hoc committee for the reevaluation of species definition in bacteriology (24) advised that all new bacterial species descriptions include an rRNA sequence from the type strain, and in 2001, Bergey's Trust published a revised higher-order taxonomy attempting to reconcile bacterial taxonomy with rRNA-based phylogeny (12, 13).The naïve Bayesian classification method is simple yet can be extremely efficient. "Naïve" refers to the (naïve) assumption that data attributes are independent. Domingos and Pazzani (11) showed that the Bayesian method can still be optimal even when this attribute independency is violated. The method has also been reported to perform well on problems similar to the classification of sequence data, such as the classification of text documents, that have a high-dimensional feature space and sparse data (16).The Ribosomal Database Project II (RDP) provides data, tools, and services related to rRNA sequences to the rese...

show abstract

Section: Discussionmentioning

confidence: 99%

Naïve Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy

Wang

Tiedje

Cole

2007

Appl Environ Microbiol

16,947

11,815

View full text Add to dashboard Cite

show abstract

“…Thereafter polymerase chain reactions (PCR) were done on randomly selected colonies from plates containing between 20 and 300 colonies (Groenewald et al 2009). The primers CC16S-F (5 0 CGT AGT TCG GAT TGC AGG C-3 0 ) and CC16S-R (5 0 GTG TTG CCG ACT CTC GTG-3 0 ) were used to amplify a 134 base pair (bp) fragment (1,254-1,388 bp) of the 16S rRNA gene (Connor et al 2005).…”

Section: Identificationmentioning

confidence: 99%

“…Graphics program: Statistica TM 9 (StatSoft, Inc., Tulsa, OK, USA). Definition: Normal line graph, color with no shading A. cycloheptanicus (Connor et al 2005). Significantly higher levels of Alicyclobacillus were recovered on fruit at the fruit washing stages when the recirculating system was operational than during the one-pass system (P \ 0.05), with 1.17-1.23 Log 10 c.f.u.…”

Section: Alicyclobacillusmentioning

confidence: 99%

Contamination of pear concentrate by Alicyclobacillus from recirculating flume water during fruit concentrate production

Steyn

Cameron

Brittin

et al. 2011

World J Microbiol Biotechnol

View full text Add to dashboard Cite

show abstract

“…and other organisms have have been reported in the literature (Al-Qadiri et al, 2006;Luo et al 2004, Jasson et al, 2009, Cagnasso et al, 2010, Connor et al, 2005, Chang and Kang 2004. Many of the published reports have, however, focused only on limited types of samples (Luo et al 2004;Connor et al, 2005). Real-time PCR-based kits which have been tested for their specificity and sensitivity are currently commercially available.…”

Section: Introductionmentioning

confidence: 99%

Fruit juice and puree characteristics influence enrichment requirements for real-time PCR detection of Alicyclobacillus acidoterrestris

Shayanfar

Harzman²,

Pillai

2015

FoodContamination

View full text Add to dashboard Cite

Background: Alicyclobacillus acidoterrestris is a key spoilage causing bacterium commonly found in fruit juices and purees. Commercial real-time PCR based assays to detect this organism are available, but reportedly require 48 hours of enrichment for detection. The underlying hypothesis of this study was that fruit juice and puree characteristics influence the enrichment requirements of this organism, and that in some matrices, the organism can be detected within 24 hours even when present at low initial contamination. Thirteen different store-purchased fruit juice and purees were inoculated with 10 CFU/ml of Alicyclobacillus acidoterrestris. The inoculated samples were enriched for 24 and 48 h. Aliquots from the un-enriched, 24 hour, and 48 hour enriched samples were taken, total community DNA extracted, and the real-time PCR assay performed using commercially available kits. Results: A. acidoterrestris was detected by real-time PCR within 24 h of enrichment in most matrices (except ketchup and orange concentrate) even from a low starting concentration (10 CFU/ml). Juice and puree samples with high soluble solids contents (i.e. Brix values) required longer incubation periods for lower A. acidoterrestris Ct values.

show abstract

Development of a real-time PCR-based system targeting the 16S rRNA gene sequence for rapid detection of Alicyclobacillus spp. in juice products

Cited by 57 publications

References 23 publications

Naïve Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy

Naïve Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy

Contamination of pear concentrate by Alicyclobacillus from recirculating flume water during fruit concentrate production

Fruit juice and puree characteristics influence enrichment requirements for real-time PCR detection of Alicyclobacillus acidoterrestris

Contact Info

Product

Resources

About